1. Field of the Invention
The present invention relates to an image enhancing system. In particular, this invention uses a perfect reconstructing filter to process image signals within a specified resolution, and enhance the image signals.
2. Description of the Related Art
Because video products have been become more popular and common over the last several decades, people can now enjoy beautiful images with excellent sound. The quality of the image is an important factor for image products. The sensing system for obtaining the image and the display system for displaying the image, are the decisive factors that determine the quality of the image. Both systems require an image processing system to make an image clearer and more vivid.
The most common method of achieving the above mentioned goal is to use a variety of filters to process the image. For example, a low pass filter is used for eliminating image noise and a high pass filter is used for enhancing the details of the image. Thereby, the user can obtain a superior image.
FIG. 1 shows a flow chart of the image processing method of the prior art. Firstly, a low pass filter 10 is used for eliminating noise of the image. Secondly, a high pass filter 12 processes the image processed by the low pass filter 10. Thirdly, a gain control unit 14 is used for enhancing the details of the image. Finally, an adder 16 is used for adding the signals processed by the low pass filter 10 and the signals processed by gain control unit 14 to obtain a final image with good quality.
The low pass filter can be a GAUSS filter or a mean-value filter. The high pass filter can bean edge-detection filter, such as a Sobel filter. The conventional image processing method needs to compromise between enhancing the details of the image and eliminating noise of the image. For example, if the noise of the image is eliminated to too great a degree, the high pass filter cannot recover details of the image. If not enough of the noise of the image is eliminated, the high pass filter amplifies the noise and the quality of the recovery image is poor.
Although the quality of the image processed by the multi-resolution filter can be enhanced, the processes required for the calculation are complex. It requires a lot of calculation processes and needs a large mass of memory.